34  Loading and preparing simulation results

34.1 πŸ“Š Analysis Pipeline for Simulation Results

πŸ’Ύ Simulation outputs: BehaviorSpace CSV files
        ↓
πŸ“₯ Import data: R, tidyverse
        ↓
🧹 Clean & prepare: Data wrangling, filtering, reshaping
        ↓
πŸ“ˆ Explore: Descriptive plots, distributions, correlations
        ↓
πŸ“Š Analyse: Statistical models, sensitivity analysis
        ↓
πŸ–ΌοΈ Visualise: Publication-ready plots, dashboard
        ↓
🧩 Interpret: Compare with hypotheses, archaeological data
        ↓
πŸ“˜ Report & share: RMarkdown, GitHub, Zenodo DOI
        β†Ί
πŸ” Refine model or experiment design

34.2 Setting up our script environment

library(ggplot2)
library(readr)
experiments_path <- "assets/netlogo/experiments/Artificial Anasazi_experiments "
color_mapping <- c("historical households" = "blue", 
                   "simulation households" = "darkred")

34.3 Single run

expname <- "experiment single run"

Read output:

results_single <- readr::read_csv(paste0(experiments_path, expname, "-table.csv"), skip = 6)
Rows: 552 Columns: 11
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (1): map-view
dbl (9): [run number], fertility, death-age, harvest-variance, fertility-end...
lgl (1): historic-view?

β„Ή Use `spec()` to retrieve the full column specification for this data.
β„Ή Specify the column types or set `show_col_types = FALSE` to quiet this message.

Plot trajectories of metrics:

plot_name <- paste0(experiments_path, expname, "-trajectories.png")

png(plot_name, width = 840, height = 540)

ggplot(results_single) +  
  geom_line(aes(x = `[step]`, y = `historical-total-households`, color = "historical data"),
            linewidth = 1.2) +
  geom_line(aes(x = `[step]`, y = `total-households`, color = "simulation households"),
            linewidth = 1.2) +
  labs(x = "steps", y = "households") +
  scale_color_manual(name = "", values = color_mapping) +
  theme(legend.position = "right")

dev.off()
svg 
  2 
knitr::include_graphics(plot_name)

34.4 Multiple runs in single configuration

expname <- "experiment multiple runs"

Read output:

results_single <- readr::read_csv(paste0(experiments_path, expname, "-table.csv"), skip = 6)
Rows: 5520 Columns: 11
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (1): map-view
dbl (9): [run number], fertility, death-age, harvest-variance, fertility-end...
lgl (1): historic-view?

β„Ή Use `spec()` to retrieve the full column specification for this data.
β„Ή Specify the column types or set `show_col_types = FALSE` to quiet this message.

Plot trajectories of metrics:

plot_name <- paste0(experiments_path, expname, "-trajectories.png")

png(plot_name, width = 840, height = 540)

ggplot(results_single) +  
  geom_line(aes(x = `[step]`, y = `total-households`, color = `[run number]`, group = `[run number]`),
            linewidth = 1.2) +
  geom_line(aes(x = `[step]`, y = `historical-total-households`), 
            color = color_mapping["historical households"],
            linewidth = 1.2, linetype = 2) +
  labs(x = "steps", y = "households") +
  theme(legend.position = "right")

dev.off()
svg 
  2 
knitr::include_graphics(plot_name)

34.5 Parameter exploration - regular intervals

34.5.1 One parameter

expname <- "experiment harvest adjustment"

Read output:

results_harvest_adj <- readr::read_csv(paste0(experiments_path, expname, "-table.csv"), skip = 6)
Rows: 104880 Columns: 11
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (1): map-view
dbl (9): [run number], fertility, death-age, harvest-variance, fertility-end...
lgl (1): historic-view?

β„Ή Use `spec()` to retrieve the full column specification for this data.
β„Ή Specify the column types or set `show_col_types = FALSE` to quiet this message.

Plot trajectories of metrics:

plot_name <- paste0(experiments_path, expname, "-trajectories.png")

png(plot_name, width = 840, height = 540)

ggplot(results_harvest_adj) +  
  geom_line(aes(x = `[step]`, y = `total-households`, color = `harvest-adjustment`, group = `[run number]`),
            linewidth = 1.2) +
  geom_line(aes(x = `[step]`, y = `historical-total-households`), color = "black",
            linewidth = 1.2, linetype = 2) +
  labs(x = "steps", y = "households") +
  theme(legend.position = "right")

dev.off()
svg 
  2 
knitr::include_graphics(plot_name)

34.5.2 Two parameter

expname <- "experiment harvest adjustment variance"

Read output:

results_harvest_adj <- readr::read_csv(paste0(experiments_path, expname, "-table.csv"), skip = 6)
Rows: 441600 Columns: 11
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (1): map-view
dbl (9): [run number], fertility, death-age, harvest-variance, fertility-end...
lgl (1): historic-view?

β„Ή Use `spec()` to retrieve the full column specification for this data.
β„Ή Specify the column types or set `show_col_types = FALSE` to quiet this message.

Plot trajectories of metrics:

plot_name <- paste0(experiments_path, expname, "-trajectories.png")

png(plot_name, width = 840, height = 540)

ggplot(results_harvest_adj) +  
  geom_line(aes(x = `[step]`, y = `total-households`, group = `[run number]`),
            color = color_mapping["simulation households"],
            linewidth = 1.2) +
  geom_line(aes(x = `[step]`, y = `historical-total-households`), 
            color = color_mapping["historical households"],
            linewidth = 1.2, linetype = 2) +
  facet_grid(`harvest-adjustment` ~ `harvest-variance`) +
  labs(x = "steps", y = "households") +
  theme(legend.position = "right")

dev.off()
svg 
  2 
knitr::include_graphics(plot_name)